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Tuesday, 6 February 2018

GLIP: A Concurrency Control Protocol for Clipping Indexing(2009)


GLIP: A Concurrency Control Protocol for 

Clipping Indexing(2009)

ABSTRACT:
            The project Concurrency Control Protocol for Clipping Indexing deals with the multidimensional databases. In multidimensional indexing trees, the overlapping of nodes will tend to degrade query performance, as one single point query may need to traverse multiple branches of the tree if the query point is in an overlapped area. Multidimensional databases are beginning to be used in a wide range of applications. To meet this fast-growing demand, the R-tree family is being applied to support fast access to multidimensional data, for which the R+-tree exhibits outstanding search performance. In order to support efficient concurrent access in multiuser environments, concurrency control mechanisms for multidimensional indexing have been proposed. However, these mechanisms cannot be directly applied to the R+-tree because an object in the R+-tree may be indexed in multiple leaves. This paper proposes a concurrency control protocol for R-tree variants with object clipping, namely, Granular Locking for clipping indexing (GLIP). GLIP is the first concurrency control approach specifically designed for the R+-tree and its variants, and it supports efficient concurrent operations with serializable isolation, consistency, and deadlock-free. Experimental tests on both real and synthetic data sets validated the effectiveness and efficiency of the proposed concurrent access framework
Existing system:
               In order to support concurrency control in R-tree structures, several approaches have been proposed, such as Partial Locking Coupling (PLC), and granular locking approaches for R-trees and GiSTs. In multidimensional indexing trees, the overlapping of nodes will tend to degrade query performance, as one single point query may need to traverse multiple branches of the tree if the query point is in an overlapped area. The R+-tree has been proposed based on modifications of the R-tree to avoid overlaps between regions at the same level, using object clipping to ensure that point queries can follow only one single search path. The R+-tree exhibits better search performance, making it suitable for applications where search is the predominant operation. For these applications, even a marginal improvement in search operations can result in significant benefits. Thus, the increased cost of updates is an acceptable price to pay.
Disadvantages
  • The R+-tree is not suitable for use with current concurrency control methods because a single object in the R+-tree may be indexed in different leaf nodes. Special considerations are needed to support concurrent queries on R+-trees.
  • While as far as we know, there is no concurrency control approach that specifically supports R+-trees.
  • Furthermore, there are some limitations in the design of the R+-tree. such as its failure to insert and split nodes in some complex overlap or intersection cases. 
Proposed system:
                   This proposes a concurrency control protocol for R-trees with object clipping, Granular Locking for clipping indexing (GLIP), to provide phantom update protection for the R+-tree and its variants. We also introduce the Zerooverlap R+-tree (ZR+-tree), which resolves the limitations of the original R+-tree by eliminating the overlaps of leaf nodes. GLIP, together with the ZR+-tree, constitutes an efficient and sound concurrent access model for multidimensional databases.
Advantages
  • The concurrency control protocol, GLIP, provides serializable isolation, consistency, and deadlock-free operations for indexing trees with object clipping.
  • The proposed multidimensional access method, ZR+-tree, utilizes object clipping, optimized insertion, and reinsert approaches to refine the indexing  structure and remove limitations in constructing and updating R+-trees.
  • GLIP and the ZR+-tree enable an efficient and sound concurrent framework to be constructed for multidimensional databases.
  • A set of extensive experiments on both real and synthetic data sets validated the efficiency and effectiveness of the proposed concurrent access framework.
Modules:
Ø  Login module
Ø  Database module
Ø  Query processing module
Ø  Lock and unlock module
Login module:
Ø  This module performs the necessary user authentication based on the username and password. 
Database module:
Ø  Using this module, one can generate the database and create the necessary tables.
Query processing module:
Ø  This module allows a user to submit a query to perform certain operation on the database.
Ø  The query uses the indexes and other structures to execute and generate the response for the user.
 Lock and unlock module:
Ø  This module implicitly locks and unlocks data items in case of concurrent access to the database.
System specifications:
Hardware specifications                    
                  .    Processor  :  Pentium IV or above
                  .    Ram             : 1GB RAM or above
                  .    Hard disk    :  40GB or above
Software specifications         
                  .     JDK5.0
                  .     Java Swings
     .     My SQL

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